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# Based on https://github.com/xinntao/Real-ESRGAN/blob/master/inference_realesrgan.py
import os
import requests
import cv2
import numpy as np
from PIL import Image
from realesrgan import RealESRGANer
from basicsr.archs.rrdbnet_arch import RRDBNet
upsampler = None
def init():
global upsampler
print("Initializing upscaler...")
if not os.path.exists("weights"):
os.mkdir("weights")
url = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth'
response = requests.get(url)
with open('weights/RealESRGAN_x2plus.pth', 'wb') as f:
f.write(response.content)
model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64,
num_block=23, num_grow_ch=32, scale=2)
upsampler = RealESRGANer(
scale=2, model_path="weights/RealESRGAN_x2plus.pth", model=model, device="cuda")
def upscale(image):
original_numpy = np.array(image)
original_opencv = cv2.cvtColor(original_numpy, cv2.COLOR_RGB2BGR)
output, _ = upsampler.enhance(original_opencv, outscale=2)
upscaled = Image.fromarray(cv2.cvtColor(output, cv2.COLOR_BGR2RGB))
return upscaled
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